CFAR data fusion of multistatic radar system under homogeneous and nonhomogeneous backgrounds

• Published in: 2002 International Radar Conference pp. 248 - 252
• Main Authors: Weixian Liu, Yilong Lu, Jeffrey, S.F
• Format: Conference Proceeding
• Language: English
• Published: London IEE 2002
• Subjects: Applied sciences; Exact sciences and technology; Information theory; Information, signal and communications theory; Optimisation techniques; Other topics in statistics; Radar theory; Radiolocalization and radionavigation; Services and terminals of telecommunications; Signal detection; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Telemetry. Remote supervision. Telewarning. Remote control; radar detection; decimal chromosomes; nonhomogeneous background; sensor fusion; approximations; nonlinear system; CFAR data fusion; search radar; genetic algorithm; optimal results; radar clutter; decentralized detection networks; OS-CFAR; surveillance system; multistatic radar system; constant false alarm rate; CA-CFAR; probability; system parameters; genetic algorithms; distributed sensors; homogeneous background; multivariable systems; detection probability; detection system performance; exhaustive search; Performance evaluation; Decentralized system; Genetic algorithm; Data fusion; Multistatic radar; Radar signal processing; Non linear system; Remote supervision; False alarm rate
• ISBN: 0852967500; 9780852967508
• ISSN: 0537-9989
• DOI: 10.1049/cp:20020286

Multistatic radar with distributed sensors and data fusion are increasingly being used by surveillance systems. The performance of the detection system mainly depends on the data fusion process. There has been a great deal of theoretical study on decentralized detection networks in homogeneous and nonhomogeneous backgrounds. To solve the resulting nonlinear system, exhaustive search and some crude approximations are adopted, however, those often cause either the system to be insensitive to some parameters or produce suboptimal results. A novel flexible genetic algorithm is investigated to obtain optimal results on constant false alarm rate data fusion. Using this approach, all system parameters are directly coded in decimal chromosomes and they can be optimized simultaneously. Furthermore, our method can also be implemented for the more general situations.